Editorial intelligence and story radar with AI

The challenge

Editorial teams need to continuously monitor a wide and fragmented volume of sources to identify facts with journalistic potential before they become evident. Relevant information can emerge in regulatory publications, public databases, press releases, and other specialized sources. Manual monitoring consumes time and makes it difficult to combine speed, breadth of coverage, and adherence to the editorial line.

The solution developed

CISP1 developed an Editorial Intelligence application that monitors selected public and regulatory sources, detects new events, and uses AI to classify themes, entities, and relevance. Identified signals are organized into a radar that allows the editorial team to focus attention on facts with the highest potential interest.

The application crosses found events with editorial context, reference content, and global trends to suggest possible story angles. Suggestions are accompanied by the sources that originated the signal, preserving journalistic verification and keeping the editorial decision with the responsible professionals.

How the application works

• Continuously monitors previously defined public and regulatory sources.
• Detects new events, changes, and potentially relevant publications.
• Classifies themes, entities, and adherence to the editorial context.
• Crosses signals with editorial references and global trends.
• Presents a prioritized radar with story suggestions and access to source materials.

Value for the operation

• Expands source coverage without requiring continuous manual reading.
• Accelerates the identification of events with journalistic potential.
• Reduces the effort of triaging dispersed information.
• Maintains traceability between the story suggestion and the sources that support it.

Capabilities applied